{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 探索有趣的问题\n",
    "- 你知道国内（不含港澳台）目前一共有多少家上市公司吗？  \n",
    "- 上市公司主要分布在哪些地方（省市）？\n",
    "- 上市公司的资产情况如何？\n",
    "- 目前上市公司的市盈率/市净率情况如何？\n",
    "- 资产规模最大/小的十家上市公司有哪些，具体规模多少？\n",
    "- 上市公司目前经营情况如何？（收入同比、利润同比、毛利率、净利润率）"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 获取数据\n",
    "主要使用tushare包获取A股所有上市公司截至目前（2018年11月26日）的基本面数据，分析相关特征和可视化，挖掘数据背后隐藏的信息。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#先引入后面可能用到的包（package）\n",
    "import pandas as pd  \n",
    "import numpy as np\n",
    "from scipy import stats\n",
    "import tushare as ts \n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline   \n",
    "\n",
    "#正常显示画图时出现的中文和负号\n",
    "from pylab import mpl\n",
    "mpl.rcParams['font.sans-serif']=['SimHei']\n",
    "mpl.rcParams['axes.unicode_minus']=False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#调取股票基本面数据和行情数据\n",
    "#基本面数据\n",
    "basics_data=ts.get_stock_basics()\n",
    "#保存数据到本地\n",
    "#basics_data.to_csv(\"basics_data.csv\",encoding='gbk')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3569, 22)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "basics_data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 数据特征  \n",
    "code,代码；\n",
    "name,名称；\n",
    "industry,细分行业；\n",
    "area,地区；\n",
    "pe,市盈率；\n",
    "outstanding,流通股本；\n",
    "totals,总股本(万)；\n",
    "totalAssets,总资产(万)；\n",
    "liquidAssets,流动资产；\n",
    "fixedAssets,固定资产；\n",
    "reserved,公积金；\n",
    "reservedPerShare,每股公积金；\n",
    "eps,每股收益；\n",
    "bvps,每股净资；\n",
    "pb,市净率；\n",
    "timeToMarket,上市日期；\n",
    "undp 未分配利润；\n",
    "perundp 每股未分配；\n",
    "rev 收入同比（%）；\n",
    "profit 利润同比（%）；\n",
    "gpr 毛利率（%）；\n",
    "npr 净利润率（%）；\n",
    "holders_num 股东人数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>industry</th>\n",
       "      <th>area</th>\n",
       "      <th>pe</th>\n",
       "      <th>outstanding</th>\n",
       "      <th>totals</th>\n",
       "      <th>totalAssets</th>\n",
       "      <th>liquidAssets</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>300752</th>\n",
       "      <td>N隆利</td>\n",
       "      <td>元器件</td>\n",
       "      <td>深圳</td>\n",
       "      <td>11.90</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.73</td>\n",
       "      <td>103243.88</td>\n",
       "      <td>87401.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002089</th>\n",
       "      <td>新 海 宜</td>\n",
       "      <td>通信设备</td>\n",
       "      <td>江苏</td>\n",
       "      <td>39.70</td>\n",
       "      <td>9.36</td>\n",
       "      <td>13.75</td>\n",
       "      <td>462289.09</td>\n",
       "      <td>186343.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002108</th>\n",
       "      <td>沧州明珠</td>\n",
       "      <td>塑料</td>\n",
       "      <td>河北</td>\n",
       "      <td>15.67</td>\n",
       "      <td>14.18</td>\n",
       "      <td>14.18</td>\n",
       "      <td>509844.59</td>\n",
       "      <td>239589.77</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name industry area     pe  outstanding  totals  totalAssets  \\\n",
       "code                                                                   \n",
       "300752    N隆利      元器件   深圳  11.90         0.18    0.73    103243.88   \n",
       "002089  新 海 宜     通信设备   江苏  39.70         9.36   13.75    462289.09   \n",
       "002108   沧州明珠       塑料   河北  15.67        14.18   14.18    509844.59   \n",
       "\n",
       "        liquidAssets  \n",
       "code                  \n",
       "300752      87401.40  \n",
       "002089     186343.20  \n",
       "002108     239589.77  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#查看前三行前8列数据\n",
    "basics_data.iloc[:3,:8]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 上市公司分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "area\n",
       "浙江    431\n",
       "江苏    400\n",
       "北京    316\n",
       "广东    304\n",
       "上海    284\n",
       "深圳    283\n",
       "山东    195\n",
       "福建    131\n",
       "四川    120\n",
       "湖南    104\n",
       "Name: name, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#使用groupby对上市公司归属地进行汇总，统计每个省份（直辖市）上市公司的总数\n",
    "area=basics_data.groupby('area')['name'].count()\n",
    "#从大到小进行排序，取出前十名\n",
    "area.sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这里发现一个bug，统计数据把广东和深圳分开了，怪不得广东排在第四呢。实际上，广东（“广东304”+“深圳283”）一共有587家上市公司，是全国在A股内上市公司最多的省份，占比高达16.47%。截至目前，深圳有283家上市公司，与上海持平，在广东占比高达48.21%，坐拥半壁江山，可见深圳的实力很强大。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "area\n",
       "广东    587\n",
       "浙江    431\n",
       "江苏    400\n",
       "北京    316\n",
       "上海    284\n",
       "山东    195\n",
       "福建    131\n",
       "四川    120\n",
       "湖南    104\n",
       "安徽    103\n",
       "Name: name, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#将“广东”与深圳数据合并成新的广东\n",
    "area['广东']=area['广东']+area['深圳']\n",
    "area.drop(['深圳'],inplace=True)\n",
    "area.sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 中国上市公司分布地图\n",
    "由于经济区域发展的不平衡，上市公司主要集中在沿海地区，那么如何在一张中国地图上反映这一情况呢？  \n",
    "这里安利一下百度的Python开源画图工具pyecharts，可以画出很酷炫的动态图。  \n",
    "下面使用pyecharts将各省（直辖市）上市公司汇总数映射到中国地图上。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "首先，安装中国省市地图包 ：   \n",
    "pip install echarts-countries-pypkg  \n",
    "pip install echarts-china-provinces-pypkg   \n",
    "pip install echarts-china-cities-pypkg   \n",
    "pip install echarts-china-counties-pypkg   \n",
    "pip install echarts-china-misc-pypkg  \n",
    "其次，安装pyecharts：  \n",
    "pip install pyecharts==0.1.9.4  \n",
    "后面那个版本号要加上，不然装好了import也会报错。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "需要安装html5的库，不然显示不了 pyecharts 的图  \n",
    "【Anaconda Prompt命令行】conda install -c anaconda html5lib\n",
    "\n",
    "【Anaconda Prompt命令行】pip install echarts-themes-pypkg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#导入作图包\n",
    "from pyecharts import Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将数据转化为字典，不转也可以\n",
    "d =dict(area)\n",
    "province=list(d.keys())\n",
    "value=list(d.values())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    require.config({\n",
       "        paths: {\n",
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       "\n",
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       "    ],\n",
       "    \"visualMap\": {\n",
       "        \"type\": \"continuous\",\n",
       "        \"min\": 12.0,\n",
       "        \"max\": 587.0,\n",
       "        \"text\": [\n",
       "            \"high\",\n",
       "            \"low\"\n",
       "        ],\n",
       "        \"textStyle\": {\n",
       "            \"color\": \"#000\"\n",
       "        },\n",
       "        \"inRange\": {\n",
       "            \"color\": [\n",
       "                \"#50a3ba\",\n",
       "                \"#eac763\",\n",
       "                \"#d94e5d\"\n",
       "            ]\n",
       "        },\n",
       "        \"calculable\": true,\n",
       "        \"splitNumber\": 5,\n",
       "        \"orient\": \"vertical\",\n",
       "        \"left\": \"left\",\n",
       "        \"top\": \"bottom\",\n",
       "        \"showLabel\": true\n",
       "    }\n",
       "};\n",
       "myChart_0a21923639d140f9b6e12c4b18e149f5.setOption(option_0a21923639d140f9b6e12c4b18e149f5);\n",
       "\n",
       "    });\n",
       "</script>\n"
      ],
      "text/plain": [
       "<pyecharts.charts.map.Map at 0x1e6e19b8be0>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#maptype='china' 只显示全国直辖市和省级\n",
    "#数据只能是省名和直辖市的名称\n",
    "map = Map(\"中国上市公司分布\", title_color=\"#fff\",\n",
    "          title_pos=\"center\", width=900, \n",
    "          height=500,background_color='#404a59')\n",
    "map.add(\"\", province, value,visual_range=[min(value),max(value)], \n",
    "       is_label_show=True,maptype='china',is_visualmap=True, \n",
    "        is_map_symbol_show=False,label_pos=\"center\",fontsize=8,\n",
    "        visual_text_color='#000')\n",
    "#map.render(path=\"中国上市公司分布.html\")\n",
    "#到所在的目录查找文件：中国上市公司分布.html\n",
    "map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "画出的是动态的中国地图（html格式），html文件使用浏览器打开，鼠标停留就能显示省市名称和上市公司个数。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下面使用柱状图对排名前十的省市进行可视化。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "#定义显示数值标签函数\n",
    "def autolabel(fig):\n",
    "    for f in fig:\n",
    "        height = f.get_height()\n",
    "        plt.text(f.get_x()+f.get_width()/2.-0.2, \n",
    "                 1.03*height, '%s' % int(height))   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "area_top=area.sort_values(ascending=False)[:10]\n",
    "d=dict(area_top)\n",
    "plt.figure(figsize=(8,5))\n",
    "fig=plt.bar(d.keys(), d.values())\n",
    "autolabel(fig)   \n",
    "plt.title(\"上市公司总数排名前十省份\",fontsize=15)\n",
    "plt.ylim(0,650)\n",
    "plt.show()\n",
    "#台湾和港澳台的没有统计进来"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "前五个省份上市公司总数占比56.57%\n",
      "前十个省份上市公司总数占比74.88%\n"
     ]
    }
   ],
   "source": [
    "#考察上市公司分布的集中度情况\n",
    "top5=(area.sort_values(ascending=False)[:5].sum()/area.sum())*100\n",
    "top10=(area.sort_values(ascending=False)[:10].sum()/area.sum())*100\n",
    "print(\"前五个省份上市公司总数占比{:.2f}%\".format(top5))\n",
    "print(\"前十个省份上市公司总数占比{:.2f}%\".format(top10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "显然，广东省是国内A股上市公司最多的省份，截至2018年11月26日，上市公司数目为587个，是排名第十安徽的5.8倍。前五个省份（直辖市）加起来一共有2017家上市公司，占全部上市公司总数的56.56%；前十个省份上市公司总数占比74.87%，可见上市公司分布的集中度比较高，主要集聚在广东、浙江、江苏、北京、上海、山东和福建沿海地区。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果将某个省（直辖市）所有上市公司的资产加总，这个排名是否不变呢？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "area\n",
       "北京    140.0676\n",
       "上海     26.3393\n",
       "深圳     23.1389\n",
       "福建      8.4503\n",
       "江苏      7.7169\n",
       "浙江      5.2406\n",
       "广东      4.5403\n",
       "山东      3.3713\n",
       "四川      1.7313\n",
       "河北      1.6175\n",
       "Name: totalAssets, dtype: float64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#对上市公司的总资产根据地区分类汇总\n",
    "totalAssets=basics_data.groupby('area')['totalAssets'].sum()\n",
    "#单位转换为万亿元，保留四位小数\n",
    "totalAssets=round(totalAssets/10**8,4) \n",
    "#排序选出前十大省市\n",
    "totalAssets.sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "同样，深圳和广东的数据是分开统计的，但有意思的是，深圳上市公司的总资产是广东（除深圳）的5倍多（amazing！）。此外，前文数据显示，北京一共有316家上市公司，全国排第四位，但其上市公司资产总和却达到140万亿元，远远超过第二名的广东（23.1+4.5=27.6亿)，是排名第9湖北的93倍，是排名最后宁夏（658亿元）的212倍，区域发展的不平衡可见一斑，财富的分布往往是遵循幂律分布的（马太效应或二八法则会不断自我强化）。北京不仅是政治和文化中心，还是经济中心，上市公司里的大型国企、央企和金融机构（如四大行）总部基本上都在北京；广东民营经济相对发达，尤其是深圳、佛山和东莞，规模不大的中小民营企业上市较多。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "area\n",
       "北京    140.0676\n",
       "广东     27.6792\n",
       "上海     26.3393\n",
       "福建      8.4503\n",
       "江苏      7.7169\n",
       "浙江      5.2406\n",
       "山东      3.3713\n",
       "四川      1.7313\n",
       "河北      1.6175\n",
       "湖北      1.5105\n",
       "Name: totalAssets, dtype: float64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#把深圳数据合并到广东\n",
    "totalAssets['广东']=totalAssets['广东']+totalAssets['深圳']\n",
    "totalAssets.drop(['深圳'],inplace=True)\n",
    "#查看前十名\n",
    "totalAssets.sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts': '/nbextensions/echarts/echarts.min', 'china': '/nbextensions/echarts-countries-js/china'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "    <div id=\"1a2bc80b25664c9ea35e893385126f83\" style=\"width:800px;height:500px;\"></div>\n",
       "\n",
       "\n",
       "<script>\n",
       "    require(['echarts', 'china'], function(echarts) {\n",
       "        \n",
       "var myChart_1a2bc80b25664c9ea35e893385126f83 = echarts.init(document.getElementById('1a2bc80b25664c9ea35e893385126f83'), 'light', {renderer: 'canvas'});\n",
       "\n",
       "var option_1a2bc80b25664c9ea35e893385126f83 = {\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"\\u4e0a\\u5e02\\u516c\\u53f8\\u603b\\u8d44\\u4ea7\\u5206\\u5e03\\u56fe\",\n",
       "            \"left\": \"center\",\n",
       "            \"top\": \"auto\",\n",
       "            \"textStyle\": {\n",
       "                \"color\": \"#fff\",\n",
       "                \"fontSize\": 18\n",
       "            },\n",
       "            \"subtextStyle\": {\n",
       "                \"fontSize\": 12\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"toolbox\": {\n",
       "        \"show\": true,\n",
       "        \"orient\": \"vertical\",\n",
       "        \"left\": \"95%\",\n",
       "        \"top\": \"center\",\n",
       "        \"feature\": {\n",
       "            \"saveAsImage\": {\n",
       "                \"show\": true,\n",
       "                \"title\": \"save as image\"\n",
       "            },\n",
       "            \"restore\": {\n",
       "                \"show\": true,\n",
       "                \"title\": \"restore\"\n",
       "            },\n",
       "            \"dataView\": {\n",
       "                \"show\": true,\n",
       "                \"title\": \"data view\"\n",
       "            }\n",
       "        }\n",
       "    },\n",
       "    \"series_id\": 3047803,\n",
       "    \"tooltip\": {\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"backgroundColor\": \"rgba(50,50,50,0.7)\",\n",
       "        \"borderColor\": \"#333\",\n",
       "        \"borderWidth\": 0\n",
       "    },\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"map\",\n",
       "            \"symbol\": \"circle\",\n",
       "            \"label\": {\n",
       "                \"normal\": {\n",
       "                    \"show\": true,\n",
       "                    \"position\": \"top\",\n",
       "                    \"textStyle\": {\n",
       "                        \"fontSize\": 12\n",
       "                    }\n",
       "                },\n",
       "                \"emphasis\": {\n",
       "                    \"show\": true,\n",
       "                    \"textStyle\": {\n",
       "                        \"fontSize\": 12\n",
       "                    }\n",
       "                }\n",
       "            },\n",
       "            \"mapType\": \"china\",\n",
       "            \"data\": [\n",
       "                {\n",
       "                    \"name\": \"\\u4e0a\\u6d77\",\n",
       "                    \"value\": 26.3393\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u4e91\\u5357\",\n",
       "                    \"value\": 0.6426\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5185\\u8499\",\n",
       "                    \"value\": 0.6201\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5317\\u4eac\",\n",
       "                    \"value\": 140.0676\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5409\\u6797\",\n",
       "                    \"value\": 0.455\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u56db\\u5ddd\",\n",
       "                    \"value\": 1.7313\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5929\\u6d25\",\n",
       "                    \"value\": 0.9014\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5b81\\u590f\",\n",
       "                    \"value\": 0.0658\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5b89\\u5fbd\",\n",
       "                    \"value\": 1.2207\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5c71\\u4e1c\",\n",
       "                    \"value\": 3.3713\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5c71\\u897f\",\n",
       "                    \"value\": 0.9204\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5e7f\\u4e1c\",\n",
       "                    \"value\": 27.6792\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5e7f\\u897f\",\n",
       "                    \"value\": 0.3764\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u65b0\\u7586\",\n",
       "                    \"value\": 1.3062\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6c5f\\u82cf\",\n",
       "                    \"value\": 7.7169\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6c5f\\u897f\",\n",
       "                    \"value\": 0.4412\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6cb3\\u5317\",\n",
       "                    \"value\": 1.6175\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6cb3\\u5357\",\n",
       "                    \"value\": 1.391\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6d59\\u6c5f\",\n",
       "                    \"value\": 5.2406\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6d77\\u5357\",\n",
       "                    \"value\": 0.433\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6e56\\u5317\",\n",
       "                    \"value\": 1.5105\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6e56\\u5357\",\n",
       "                    \"value\": 1.4924\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u7518\\u8083\",\n",
       "                    \"value\": 0.2883\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u798f\\u5efa\",\n",
       "                    \"value\": 8.4503\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u897f\\u85cf\",\n",
       "                    \"value\": 0.0747\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u8d35\\u5dde\",\n",
       "                    \"value\": 0.8858\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u8fbd\\u5b81\",\n",
       "                    \"value\": 1.1896\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u91cd\\u5e86\",\n",
       "                    \"value\": 0.8801\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u9655\\u897f\",\n",
       "                    \"value\": 0.6933\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u9752\\u6d77\",\n",
       "                    \"value\": 0.1911\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u9ed1\\u9f99\\u6c5f\",\n",
       "                    \"value\": 0.613\n",
       "                }\n",
       "            ],\n",
       "            \"roam\": true,\n",
       "            \"showLegendSymbol\": false\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\"\n",
       "            ],\n",
       "            \"selectedMode\": \"multiple\",\n",
       "            \"show\": true,\n",
       "            \"left\": \"center\",\n",
       "            \"top\": \"top\",\n",
       "            \"orient\": \"horizontal\",\n",
       "            \"textStyle\": {\n",
       "                \"fontSize\": 12\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"backgroundColor\": \"#404a59\",\n",
       "    \"animation\": true,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\",\n",
       "        \"#f6f5ec\"\n",
       "    ],\n",
       "    \"visualMap\": {\n",
       "        \"type\": \"continuous\",\n",
       "        \"min\": 0.0658,\n",
       "        \"max\": 140.0676,\n",
       "        \"text\": [\n",
       "            \"high\",\n",
       "            \"low\"\n",
       "        ],\n",
       "        \"textStyle\": {\n",
       "            \"color\": \"#000\"\n",
       "        },\n",
       "        \"inRange\": {\n",
       "            \"color\": [\n",
       "                \"#50a3ba\",\n",
       "                \"#eac763\",\n",
       "                \"#d94e5d\"\n",
       "            ]\n",
       "        },\n",
       "        \"calculable\": true,\n",
       "        \"splitNumber\": 5,\n",
       "        \"orient\": \"vertical\",\n",
       "        \"left\": \"left\",\n",
       "        \"top\": \"bottom\",\n",
       "        \"showLabel\": true\n",
       "    }\n",
       "};\n",
       "myChart_1a2bc80b25664c9ea35e893385126f83.setOption(option_1a2bc80b25664c9ea35e893385126f83);\n",
       "\n",
       "    });\n",
       "</script>\n"
      ],
      "text/plain": [
       "<pyecharts.charts.map.Map at 0x1e6e1d0d198>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#地图可视化\n",
    "#d =dict(totalAssets)\n",
    "#x=list(d.keys())\n",
    "#y=list(d.values())\n",
    "\n",
    "x=totalAssets.index\n",
    "y=totalAssets.values\n",
    "\n",
    "map = Map(\"上市公司总资产分布图\", title_color=\"#fff\",\n",
    "          title_pos=\"center\", width=800, height=500,\n",
    "          background_color='#404a59')\n",
    "map.add(\"\", x, y, maptype='china',is_visualmap=True,\n",
    "        is_map_symbol_show=False,\n",
    "        is_label_show=True,visual_range=[min(y),max(y)],\n",
    "        visual_text_color='#000')\n",
    "#map.render(path=\"上市公司总资产分布图.html\")\n",
    "map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def autolabel(fig):\n",
    "    for f in fig:\n",
    "        height = f.get_height()\n",
    "        plt.text(f.get_x()+f.get_width()/2.-0.2, \n",
    "                 1.03*height, '%s' % round(float(height),2))   \n",
    "\n",
    "TA_top=totalAssets.sort_values(ascending=False)[:10]\n",
    "d=dict(TA_top)\n",
    "plt.figure(figsize=(8,5))\n",
    "fig=plt.bar(d.keys(), d.values())\n",
    "autolabel(fig)   \n",
    "plt.title(\"上市公司总资产排名前十省份\",fontsize=15)\n",
    "plt.ylim(0,150)\n",
    "plt.ylabel('万亿元')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 特征挖掘\n",
    "下面继续对A股所有上市公司的市盈率（pe）、市净率（pb）、总资产（totalAssets,万元）、每股收益（eps）rev 收入同比（%）； profit 利润同比（%）； gpr 毛利率（%）； npr 净利润率（%）分别进行排序对比。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>industry</th>\n",
       "      <th>pe</th>\n",
       "      <th>pb</th>\n",
       "      <th>totalAssets</th>\n",
       "      <th>esp</th>\n",
       "      <th>rev</th>\n",
       "      <th>profit</th>\n",
       "      <th>gpr</th>\n",
       "      <th>npr</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>300370</th>\n",
       "      <td>安控科技</td>\n",
       "      <td>电器仪表</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.06</td>\n",
       "      <td>468268.16</td>\n",
       "      <td>-0.009</td>\n",
       "      <td>-3.81</td>\n",
       "      <td>-140.41</td>\n",
       "      <td>35.40</td>\n",
       "      <td>-1.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600310</th>\n",
       "      <td>桂东电力</td>\n",
       "      <td>水力发电</td>\n",
       "      <td>281.62</td>\n",
       "      <td>2.06</td>\n",
       "      <td>1477545.88</td>\n",
       "      <td>0.012</td>\n",
       "      <td>31.58</td>\n",
       "      <td>-44.49</td>\n",
       "      <td>5.78</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300310</th>\n",
       "      <td>宜通世纪</td>\n",
       "      <td>通信设备</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.43</td>\n",
       "      <td>382517.84</td>\n",
       "      <td>-0.645</td>\n",
       "      <td>9.88</td>\n",
       "      <td>-454.81</td>\n",
       "      <td>16.28</td>\n",
       "      <td>-30.91</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name industry      pe    pb  totalAssets    esp    rev  profit    gpr  \\\n",
       "code                                                                            \n",
       "300370  安控科技     电器仪表    0.00  2.06    468268.16 -0.009  -3.81 -140.41  35.40   \n",
       "600310  桂东电力     水力发电  281.62  2.06   1477545.88  0.012  31.58  -44.49   5.78   \n",
       "300310  宜通世纪     通信设备    0.00  1.43    382517.84 -0.645   9.88 -454.81  16.28   \n",
       "\n",
       "          npr  \n",
       "code           \n",
       "300370  -1.13  \n",
       "600310   0.10  \n",
       "300310 -30.91  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#保留需要分析的特征数据\n",
    "d=['name','industry','pe','pb','totalAssets','esp','rev','profit','gpr','npr']\n",
    "df=basics_data[d]\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pe</th>\n",
       "      <th>pb</th>\n",
       "      <th>totalAssets</th>\n",
       "      <th>esp</th>\n",
       "      <th>rev</th>\n",
       "      <th>profit</th>\n",
       "      <th>gpr</th>\n",
       "      <th>npr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3566.00</td>\n",
       "      <td>3566.00</td>\n",
       "      <td>3.566000e+03</td>\n",
       "      <td>3566.00</td>\n",
       "      <td>3566.00</td>\n",
       "      <td>3566.00</td>\n",
       "      <td>3566.00</td>\n",
       "      <td>3566.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>69.06</td>\n",
       "      <td>1.73</td>\n",
       "      <td>6.696720e+06</td>\n",
       "      <td>0.33</td>\n",
       "      <td>23.54</td>\n",
       "      <td>15.53</td>\n",
       "      <td>29.34</td>\n",
       "      <td>-3.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>274.48</td>\n",
       "      <td>133.52</td>\n",
       "      <td>8.705875e+07</td>\n",
       "      <td>0.57</td>\n",
       "      <td>141.85</td>\n",
       "      <td>776.86</td>\n",
       "      <td>23.56</td>\n",
       "      <td>409.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.00</td>\n",
       "      <td>-7502.77</td>\n",
       "      <td>4.843750e+03</td>\n",
       "      <td>-4.56</td>\n",
       "      <td>-100.14</td>\n",
       "      <td>-32637.62</td>\n",
       "      <td>-779.78</td>\n",
       "      <td>-17764.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>14.06</td>\n",
       "      <td>1.38</td>\n",
       "      <td>1.823460e+05</td>\n",
       "      <td>0.07</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-22.16</td>\n",
       "      <td>16.72</td>\n",
       "      <td>2.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>24.74</td>\n",
       "      <td>2.08</td>\n",
       "      <td>4.099019e+05</td>\n",
       "      <td>0.22</td>\n",
       "      <td>12.07</td>\n",
       "      <td>9.83</td>\n",
       "      <td>26.58</td>\n",
       "      <td>7.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>45.56</td>\n",
       "      <td>3.17</td>\n",
       "      <td>1.063947e+06</td>\n",
       "      <td>0.45</td>\n",
       "      <td>27.66</td>\n",
       "      <td>43.58</td>\n",
       "      <td>39.29</td>\n",
       "      <td>14.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>7897.70</td>\n",
       "      <td>2422.68</td>\n",
       "      <td>2.819813e+09</td>\n",
       "      <td>19.69</td>\n",
       "      <td>5053.27</td>\n",
       "      <td>18509.93</td>\n",
       "      <td>99.85</td>\n",
       "      <td>1332.62</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            pe       pb   totalAssets      esp      rev    profit      gpr  \\\n",
       "count  3566.00  3566.00  3.566000e+03  3566.00  3566.00   3566.00  3566.00   \n",
       "mean     69.06     1.73  6.696720e+06     0.33    23.54     15.53    29.34   \n",
       "std     274.48   133.52  8.705875e+07     0.57   141.85    776.86    23.56   \n",
       "min       0.00 -7502.77  4.843750e+03    -4.56  -100.14 -32637.62  -779.78   \n",
       "25%      14.06     1.38  1.823460e+05     0.07     0.00    -22.16    16.72   \n",
       "50%      24.74     2.08  4.099019e+05     0.22    12.07      9.83    26.58   \n",
       "75%      45.56     3.17  1.063947e+06     0.45    27.66     43.58    39.29   \n",
       "max    7897.70  2422.68  2.819813e+09    19.69  5053.27  18509.93    99.85   \n",
       "\n",
       "            npr  \n",
       "count   3566.00  \n",
       "mean      -3.34  \n",
       "std      409.48  \n",
       "min   -17764.19  \n",
       "25%        2.90  \n",
       "50%        7.70  \n",
       "75%       14.35  \n",
       "max     1332.62  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#描述性统计\n",
    "df.describe().round(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从描述性统计上可以看出，一共统计了3565只股票数据，市盈率（pe，即股价/每股收益）均值为68.42，可能是受极端值影响，平均值很难反映出总体情况。实际上，市盈率的25%分位数点只有14.03，50%分位数点只有24.48。如果分版块来看（此处没有给出Python代码），上证板块的动态市盈率11倍左右，深证板块21倍左右，创业板37倍左右，基本上处于历史相对低位了。市净率（pb，即股价/账面价值）均值为1.68，中位数为2.07。市盈率对微利或者亏损的公司而言并不适用，但是微利或者亏损的公司仍然可以使用市净率进行评估，除非公司资不抵债。我们注意到pb的最小值居然为-7591，这应该是异常值！总资产均值为670亿元左右，上市公司总资产最小的只有4843万元，而最大的高达28198亿元，看来都是被平均了。对于资产（财富）的分布使用平均值容易误导人。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>industry</th>\n",
       "      <th>pe</th>\n",
       "      <th>pb</th>\n",
       "      <th>totalAssets</th>\n",
       "      <th>esp</th>\n",
       "      <th>rev</th>\n",
       "      <th>profit</th>\n",
       "      <th>gpr</th>\n",
       "      <th>npr</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>002260</th>\n",
       "      <td>*ST德奥</td>\n",
       "      <td>航空</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-4.46</td>\n",
       "      <td>54416.53</td>\n",
       "      <td>-0.241</td>\n",
       "      <td>-5.85</td>\n",
       "      <td>-54.04</td>\n",
       "      <td>18.22</td>\n",
       "      <td>-11.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600198</th>\n",
       "      <td>*ST大唐</td>\n",
       "      <td>通信设备</td>\n",
       "      <td>18.25</td>\n",
       "      <td>-49.14</td>\n",
       "      <td>794417.88</td>\n",
       "      <td>0.286</td>\n",
       "      <td>-59.41</td>\n",
       "      <td>149.85</td>\n",
       "      <td>26.06</td>\n",
       "      <td>16.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000995</th>\n",
       "      <td>*ST皇台</td>\n",
       "      <td>白酒</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-5.64</td>\n",
       "      <td>23513.60</td>\n",
       "      <td>-0.236</td>\n",
       "      <td>-76.61</td>\n",
       "      <td>37.82</td>\n",
       "      <td>-49.40</td>\n",
       "      <td>-440.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002188</th>\n",
       "      <td>*ST巴士</td>\n",
       "      <td>广告包装</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-2.05</td>\n",
       "      <td>60855.93</td>\n",
       "      <td>-1.684</td>\n",
       "      <td>-78.68</td>\n",
       "      <td>-816.16</td>\n",
       "      <td>-73.34</td>\n",
       "      <td>-474.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600870</th>\n",
       "      <td>*ST厦华</td>\n",
       "      <td>家用电器</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-345.26</td>\n",
       "      <td>6048.43</td>\n",
       "      <td>-0.016</td>\n",
       "      <td>782.26</td>\n",
       "      <td>-52.05</td>\n",
       "      <td>10.78</td>\n",
       "      <td>-26.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600074</th>\n",
       "      <td>*ST保千</td>\n",
       "      <td>电脑设备</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.86</td>\n",
       "      <td>184855.02</td>\n",
       "      <td>-0.150</td>\n",
       "      <td>-96.10</td>\n",
       "      <td>-190.85</td>\n",
       "      <td>20.87</td>\n",
       "      <td>-317.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000953</th>\n",
       "      <td>ST河化</td>\n",
       "      <td>农药化肥</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-15.90</td>\n",
       "      <td>54516.43</td>\n",
       "      <td>-0.332</td>\n",
       "      <td>4.13</td>\n",
       "      <td>-32637.62</td>\n",
       "      <td>-16.05</td>\n",
       "      <td>-45.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002604</th>\n",
       "      <td>*ST龙力</td>\n",
       "      <td>食品</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-1.78</td>\n",
       "      <td>381058.53</td>\n",
       "      <td>-0.423</td>\n",
       "      <td>-37.50</td>\n",
       "      <td>-317.98</td>\n",
       "      <td>20.69</td>\n",
       "      <td>-37.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600186</th>\n",
       "      <td>莲花健康</td>\n",
       "      <td>食品</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-34.48</td>\n",
       "      <td>185969.45</td>\n",
       "      <td>-0.094</td>\n",
       "      <td>-6.20</td>\n",
       "      <td>8.91</td>\n",
       "      <td>11.02</td>\n",
       "      <td>-7.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600877</th>\n",
       "      <td>ST嘉陵</td>\n",
       "      <td>摩托车</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-19.07</td>\n",
       "      <td>100063.36</td>\n",
       "      <td>-0.235</td>\n",
       "      <td>-30.77</td>\n",
       "      <td>-607.95</td>\n",
       "      <td>1.03</td>\n",
       "      <td>-52.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000927</th>\n",
       "      <td>一汽夏利</td>\n",
       "      <td>汽车整车</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-5.77</td>\n",
       "      <td>456620.44</td>\n",
       "      <td>-0.629</td>\n",
       "      <td>-5.49</td>\n",
       "      <td>10.73</td>\n",
       "      <td>-25.04</td>\n",
       "      <td>-106.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000585</th>\n",
       "      <td>*ST东电</td>\n",
       "      <td>电气设备</td>\n",
       "      <td>42.04</td>\n",
       "      <td>-11.07</td>\n",
       "      <td>30083.40</td>\n",
       "      <td>0.037</td>\n",
       "      <td>-3.67</td>\n",
       "      <td>216.80</td>\n",
       "      <td>19.29</td>\n",
       "      <td>150.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600399</th>\n",
       "      <td>*ST抚钢</td>\n",
       "      <td>特种钢</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-3.25</td>\n",
       "      <td>850870.13</td>\n",
       "      <td>-0.097</td>\n",
       "      <td>5.60</td>\n",
       "      <td>-287.01</td>\n",
       "      <td>8.96</td>\n",
       "      <td>-2.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000737</th>\n",
       "      <td>*ST南风</td>\n",
       "      <td>日用化工</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>311601.06</td>\n",
       "      <td>-0.297</td>\n",
       "      <td>3.99</td>\n",
       "      <td>35.45</td>\n",
       "      <td>24.27</td>\n",
       "      <td>-10.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600961</th>\n",
       "      <td>株冶集团</td>\n",
       "      <td>铅锌</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-2.99</td>\n",
       "      <td>557306.50</td>\n",
       "      <td>-2.979</td>\n",
       "      <td>-11.22</td>\n",
       "      <td>-3749.51</td>\n",
       "      <td>-2.61</td>\n",
       "      <td>-17.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>002306</th>\n",
       "      <td>*ST云网</td>\n",
       "      <td>酒店餐饮</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-7502.77</td>\n",
       "      <td>8161.31</td>\n",
       "      <td>-0.020</td>\n",
       "      <td>-20.05</td>\n",
       "      <td>-25.95</td>\n",
       "      <td>42.10</td>\n",
       "      <td>-26.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300104</th>\n",
       "      <td>乐视网</td>\n",
       "      <td>互联网</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-33.36</td>\n",
       "      <td>1637194.75</td>\n",
       "      <td>-0.373</td>\n",
       "      <td>-77.88</td>\n",
       "      <td>9.82</td>\n",
       "      <td>-39.42</td>\n",
       "      <td>-110.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name industry     pe       pb  totalAssets    esp     rev    profit  \\\n",
       "code                                                                           \n",
       "002260  *ST德奥       航空   0.00    -4.46     54416.53 -0.241   -5.85    -54.04   \n",
       "600198  *ST大唐     通信设备  18.25   -49.14    794417.88  0.286  -59.41    149.85   \n",
       "000995  *ST皇台       白酒   0.00    -5.64     23513.60 -0.236  -76.61     37.82   \n",
       "002188  *ST巴士     广告包装   0.00    -2.05     60855.93 -1.684  -78.68   -816.16   \n",
       "600870  *ST厦华     家用电器   0.00  -345.26      6048.43 -0.016  782.26    -52.05   \n",
       "600074  *ST保千     电脑设备   0.00    -0.86    184855.02 -0.150  -96.10   -190.85   \n",
       "000953   ST河化     农药化肥   0.00   -15.90     54516.43 -0.332    4.13 -32637.62   \n",
       "002604  *ST龙力       食品   0.00    -1.78    381058.53 -0.423  -37.50   -317.98   \n",
       "600186   莲花健康       食品   0.00   -34.48    185969.45 -0.094   -6.20      8.91   \n",
       "600877   ST嘉陵      摩托车   0.00   -19.07    100063.36 -0.235  -30.77   -607.95   \n",
       "000927   一汽夏利     汽车整车   0.00    -5.77    456620.44 -0.629   -5.49     10.73   \n",
       "000585  *ST东电     电气设备  42.04   -11.07     30083.40  0.037   -3.67    216.80   \n",
       "600399  *ST抚钢      特种钢   0.00    -3.25    850870.13 -0.097    5.60   -287.01   \n",
       "000737  *ST南风     日用化工   0.00    -3.75    311601.06 -0.297    3.99     35.45   \n",
       "600961   株冶集团       铅锌   0.00    -2.99    557306.50 -2.979  -11.22  -3749.51   \n",
       "002306  *ST云网     酒店餐饮   0.00 -7502.77      8161.31 -0.020  -20.05    -25.95   \n",
       "300104    乐视网      互联网   0.00   -33.36   1637194.75 -0.373  -77.88      9.82   \n",
       "\n",
       "          gpr     npr  \n",
       "code                   \n",
       "002260  18.22  -11.80  \n",
       "600198  26.06   16.06  \n",
       "000995 -49.40 -440.96  \n",
       "002188 -73.34 -474.00  \n",
       "600870  10.78  -26.65  \n",
       "600074  20.87 -317.26  \n",
       "000953 -16.05  -45.09  \n",
       "002604  20.69  -37.52  \n",
       "600186  11.02   -7.67  \n",
       "600877   1.03  -52.17  \n",
       "000927 -25.04 -106.42  \n",
       "000585  19.29  150.73  \n",
       "600399   8.96   -2.90  \n",
       "000737  24.27  -10.74  \n",
       "600961  -2.61  -17.52  \n",
       "002306  42.10  -26.84  \n",
       "300104 -39.42 -110.50  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#查看pb为负数的股票\n",
    "df[df.pb<0]\n",
    "#基本上都是st股票，乐视网赫然在列\n",
    "#这些公司经营亏到妈都不认得，大部分财务指标都是负数，不堪入目。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pe</th>\n",
       "      <th>pb</th>\n",
       "      <th>totalAssets</th>\n",
       "      <th>esp</th>\n",
       "      <th>rev</th>\n",
       "      <th>profit</th>\n",
       "      <th>gpr</th>\n",
       "      <th>npr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3205.00</td>\n",
       "      <td>3205.00</td>\n",
       "      <td>3.205000e+03</td>\n",
       "      <td>3205.00</td>\n",
       "      <td>3205.00</td>\n",
       "      <td>3205.00</td>\n",
       "      <td>3205.00</td>\n",
       "      <td>3205.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>76.82</td>\n",
       "      <td>2.76</td>\n",
       "      <td>7.366348e+06</td>\n",
       "      <td>0.39</td>\n",
       "      <td>22.95</td>\n",
       "      <td>72.94</td>\n",
       "      <td>30.88</td>\n",
       "      <td>12.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>288.50</td>\n",
       "      <td>4.05</td>\n",
       "      <td>9.180673e+07</td>\n",
       "      <td>0.56</td>\n",
       "      <td>85.37</td>\n",
       "      <td>483.15</td>\n",
       "      <td>18.58</td>\n",
       "      <td>29.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.64</td>\n",
       "      <td>0.55</td>\n",
       "      <td>7.015800e+03</td>\n",
       "      <td>-0.06</td>\n",
       "      <td>-95.39</td>\n",
       "      <td>-99.52</td>\n",
       "      <td>-85.14</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>16.80</td>\n",
       "      <td>1.40</td>\n",
       "      <td>1.920446e+05</td>\n",
       "      <td>0.12</td>\n",
       "      <td>1.92</td>\n",
       "      <td>-12.25</td>\n",
       "      <td>17.86</td>\n",
       "      <td>4.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>27.60</td>\n",
       "      <td>2.07</td>\n",
       "      <td>4.296592e+05</td>\n",
       "      <td>0.25</td>\n",
       "      <td>13.46</td>\n",
       "      <td>12.78</td>\n",
       "      <td>27.88</td>\n",
       "      <td>8.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>49.88</td>\n",
       "      <td>3.11</td>\n",
       "      <td>1.127149e+06</td>\n",
       "      <td>0.49</td>\n",
       "      <td>28.77</td>\n",
       "      <td>47.90</td>\n",
       "      <td>40.25</td>\n",
       "      <td>15.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>7897.70</td>\n",
       "      <td>149.99</td>\n",
       "      <td>2.819813e+09</td>\n",
       "      <td>19.69</td>\n",
       "      <td>2920.96</td>\n",
       "      <td>18509.93</td>\n",
       "      <td>99.85</td>\n",
       "      <td>1332.62</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            pe       pb   totalAssets      esp      rev    profit      gpr  \\\n",
       "count  3205.00  3205.00  3.205000e+03  3205.00  3205.00   3205.00  3205.00   \n",
       "mean     76.82     2.76  7.366348e+06     0.39    22.95     72.94    30.88   \n",
       "std     288.50     4.05  9.180673e+07     0.56    85.37    483.15    18.58   \n",
       "min       2.64     0.55  7.015800e+03    -0.06   -95.39    -99.52   -85.14   \n",
       "25%      16.80     1.40  1.920446e+05     0.12     1.92    -12.25    17.86   \n",
       "50%      27.60     2.07  4.296592e+05     0.25    13.46     12.78    27.88   \n",
       "75%      49.88     3.11  1.127149e+06     0.49    28.77     47.90    40.25   \n",
       "max    7897.70   149.99  2.819813e+09    19.69  2920.96  18509.93    99.85   \n",
       "\n",
       "           npr  \n",
       "count  3205.00  \n",
       "mean     12.92  \n",
       "std      29.79  \n",
       "min       0.02  \n",
       "25%       4.26  \n",
       "50%       8.65  \n",
       "75%      15.22  \n",
       "max    1332.62  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#对数据进一步清洗\n",
    "#剔除掉市盈率为负数或0的股票\n",
    "df=df[df.pe>0]\n",
    "#剔除掉市净率为负数的股票\n",
    "df=df[df.pb>0]\n",
    "df.describe().round(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "不难理解，剔除掉负的pe和pb后，二者的均值提高了，实际上剩余股票pe的75%分位点只有49.88，均值主要是极端值拉高的。当然，从实际投资角度看，pe和pb指标并非单纯的越小越好，并且不同行业这两项指标可比性较差。股票定价是基于对未来的预期，pe和pb小可能只是反映了未来没什么故事可讲，增长空间有限，而pe和pb比较大甚至为负反而为未来业绩改善提供了很多想象空间（这也常常成为游资大佬收割韭菜的题材炒作手段）。不过值得留意的是，如果是在经济低迷或者黑天鹅事件冲击造成股市恐慌性下跌，不少业绩好的股票很可能被错杀，股价大跌，导致pe和pb较小，这种股票是价值投资里值得深入挖掘的标的。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 可视化分析\n",
    "寻找上市公司十大之最。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#定义一个画图函数\n",
    "def plot_data(data,title):\n",
    "    d=dict(data)\n",
    "    plt.figure(figsize=(8,5))\n",
    "    fig=plt.bar(d.keys(), d.values())\n",
    "    autolabel(fig)   \n",
    "    plt.title(title,fontsize=15)\n",
    "    plt.ylim(0,max(d.values())*1.1)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#查看十大最低市盈率行业\n",
    "#这里行业划分不是很严谨，直接从数据库导出的\n",
    "pe_ind=df.groupby('industry')['pe'].mean()\n",
    "pe=pe_ind.sort_values()[:10].round(2)\n",
    "title='十大最低市盈率行业'\n",
    "plot_data(pe,title)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "银行的市盈率是所有行业（这里行业分类比较细）里最低的，平均为6.78左右，其实不说你也知道：银行是中国上市公司里最赚钱的！但是，银行股可能因为盘子太大，短期走势就像心电图，所以散户一般是敬而远之。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#查看十大最高市盈率行业\n",
    "pe_ind1=df.groupby('industry')['pe'].mean()\n",
    "pe1=pe_ind.sort_values(ascending=False)[:10].round(2)\n",
    "title1='十大最高市盈率行业'\n",
    "plot_data(pe1,title1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#查看十大最低市净率公司\n",
    "pb=df['pb']\n",
    "pb.index=df['name']\n",
    "pb10=pb.sort_values(ascending=True)[:10].round(2)\n",
    "title='十大最低市净率公司'\n",
    "plot_data(pb10,title)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "市净率低于1公司个数：280\n"
     ]
    }
   ],
   "source": [
    "#查看市净率小于1的公司个数\n",
    "n=df['pb'][df.pb<1].count()\n",
    "print(\"市净率低于1公司个数：{:}\".format(n))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "市净率是每股净资产与实时股价的比值，市净率小于1相当于公司以低于净资产的价格出售。一般而言，上市公司为了回避被隐性对手低价收购会尽力拉升股价。\n",
    "但市净率小于1不一定就是好股票，还是要考察公司未来几年的业绩。市净率小于1的股票绝大多数会涨的，但股价弹性比较小，波动性也相对更小。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#查看总资产最大的十家上市公司（万亿元）\n",
    "TA=(df['totalAssets']/10**8).round(2)\n",
    "TA.index=df['name']\n",
    "TA10=TA.sort_values(ascending=False)[:10]\n",
    "title='总资产最大的十家上市公司(万亿元)'\n",
    "plot_data(TA10,title)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "工商银行资产占全部上市公司的比重为：12.07%\n",
      "四大银行资产占全部上市公司的比重为：40.75%\n"
     ]
    }
   ],
   "source": [
    "icbc=(TA['工商银行']/TA.sum())*100\n",
    "bank4=(TA[['工商银行','建设银行','农业银行','中国银行']].sum()/TA.sum())*100\n",
    "print(\"工商银行资产占全部上市公司的比重为：{:.2f}%\".format(icbc))\n",
    "print(\"四大银行资产占全部上市公司的比重为：{:.2f}%\".format(bank4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "总资产排名前十的都是银行（除平安是综合金融），而四大银行的资产规模庞大到惊人，工商银行总资产为28.2万亿元。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#再来看看总资产最小的十家上市公司（百万元）\n",
    "TA1=(df['totalAssets']/100).round(2)\n",
    "TA1.index=df['name']\n",
    "TA2=TA1.sort_values(ascending=True)[:10]\n",
    "title1='资产最小的十家上市公司(百万元)'\n",
    "plot_data(TA2,title1)\n",
    "#注意：这里是剔除了某些异常值后的数据结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#每股收益最大的十家上市公司\n",
    "esp=(df['esp'])\n",
    "esp.index=df['name']\n",
    "esp10=esp.sort_values(ascending=False)[:10]\n",
    "title='每股收益最大的十家上市公司'\n",
    "plot_data(esp10,title)\n",
    "#贵州茅台一枝独秀，遥遥领先\n",
    "#下面几家公司就是传说中的白马股啦\n",
    "#白马股特征：长期绩优、回报率高并具有较高投资价值的股票"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x0 = esp10.index   #横坐标\n",
    "y = esp10.values   #第一个纵坐标\n",
    "y1 =pe1.values   #第二个纵坐标\n",
    "x = np.arange(len(x))  #首先用第一个的长度作为横坐标\n",
    "width = 0.4    #设置柱与柱之间的宽度\n",
    "fig,ax1 = plt.subplots(figsize=(8,5))\n",
    "ax1.bar(x,y,width,alpha = 0.9,label='每股收益')\n",
    "plt.legend(loc='upper center')\n",
    "ax2 = ax1.twinx()\n",
    "ax2.bar(x+width,y1,width,alpha = 0.9,color= 'red',label='市盈率')\n",
    "ax1.set_xticks(x +width/2)#将坐标设置在指定位置\n",
    "ax1.set_xticklabels(x0)#将横坐标替换成\n",
    "plt.legend(loc=0)\n",
    "plt.title(\"每股收益最大的十家上市公司市盈率\",fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#利润同比最大的十家上市公司（%）\n",
    "profit=(df['profit'])\n",
    "profit.index=df['name']\n",
    "profit10=profit.sort_values(ascending=False)[:10]\n",
    "title='利润同比最大的十家上市公司(%)'\n",
    "plot_data(profit10,title)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#净利率同比最大的十家上市公司（%）\n",
    "npr=(df['npr'])\n",
    "npr.index=df['name']\n",
    "npr10=npr.sort_values(ascending=False)[:10]\n",
    "title='净利率同比最大的十家上市公司(%)'\n",
    "plot_data(npr10,title)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
